A Greedy Subspace Method for Computing the ℒ∞‐Norm. Issue 1 (15th March 2018) - Aliyev, Nicat; Benner, Peter; Mengi, Emre; Schwerdtner, Paul; Voigt, Matthias
Abstract: We consider the computation of the ℒ∞ ‐norm for a general class of ℒ∞ ‐functions and focus on the case where the function is represented in terms of large‐scale matrix‐valued factors. We propose a subspace projection method to obtain reduced approximations of this function by interpolation techniques. The ℒ∞ ‐norms are computed for the resulting reduced functions, then the subspaces are refined by means of the optimizer of the ℒ∞ ‐norm of the reduced function. In this way we obtain much better performance compared to existing methods. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)